Adaptive channel equalization for satellite communications with multipath based on unsupervised learning algorithm

Channel equalization has been revealed to be a classification problem by some recent applications of clustering and neural network techniques. In this paper, a new unsupervised learning (clustering) algorithm, adaptive nearest neighbor classifier (ANNC) is presented for channel equalization. ANNC can mine more channel characteristics that the recently proposed nearest neighbor (NNC) classifier. The proposed method is applied to a time-division-multiple-access (TDMA) satellite communication system with burst digital transmission. The improvement of the proposed algorithm over the recently reported NNC approach is clearly demonstrated.